| Title |
Blood flow mechanics and oxygen transport and delivery in the retinal microcirculation: multiscale mathematical modeling and numerical simulation
|
|---|---|
| Published in |
Biomechanics and Modeling in Mechanobiology, August 2015
|
| DOI | 10.1007/s10237-015-0708-7 |
| Pubmed ID | |
| Authors |
Paola Causin, Giovanna Guidoboni, Francesca Malgaroli, Riccardo Sacco, Alon Harris |
| Abstract |
The scientific community continues to accrue evidence that blood flow alterations and ischemic conditions in the retina play an important role in the pathogenesis of ocular diseases. Many factors influence retinal hemodynamics and tissue oxygenation, including blood pressure, blood rheology, oxygen arterial permeability and tissue metabolic demand. Since the influence of these factors on the retinal circulation is difficult to isolate in vivo, we propose here a novel mathematical and computational model describing the coupling between blood flow mechanics and oxygen ([Formula: see text]) transport in the retina. Albeit in a simplified manner, the model accounts for the three-dimensional anatomical structure of the retina, consisting in a layered tissue nourished by an arteriolar/venular network laying on the surface proximal to the vitreous. Capillary plexi, originating from terminal arterioles and converging into smaller venules, are embedded in two distinct tissue layers. Arteriolar and venular networks are represented by fractal trees, whereas capillary plexi are represented using a simplified lumped description. In the model, [Formula: see text] is transported along the vasculature and delivered to the tissue at a rate that depends on the metabolic demand of the various tissue layers. First, the model is validated against available experimental results to identify baseline conditions. Then, a sensitivity analysis is performed to quantify the influence of blood pressure, blood rheology, oxygen arterial permeability and tissue oxygen demand on the [Formula: see text] distribution within the blood vessels and in the tissue. This analysis shows that: (1) systemic arterial blood pressure has a strong influence on the [Formula: see text] profiles in both blood and tissue; (2) plasma viscosity and metabolic consumption rates have a strong influence on the [Formula: see text] tension at the level of the retinal ganglion cells; and (3) arterial [Formula: see text] permeability has a strong influence on the [Formula: see text] saturation in the retinal arterioles. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 1 | 2% |
| Unknown | 63 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 17% |
| Student > Master | 9 | 14% |
| Researcher | 8 | 13% |
| Student > Bachelor | 6 | 9% |
| Student > Doctoral Student | 4 | 6% |
| Other | 11 | 17% |
| Unknown | 15 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 20 | 31% |
| Medicine and Dentistry | 8 | 13% |
| Physics and Astronomy | 5 | 8% |
| Mathematics | 4 | 6% |
| Biochemistry, Genetics and Molecular Biology | 2 | 3% |
| Other | 10 | 16% |
| Unknown | 15 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 October 2017.
All research outputs
#21,186,729
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Outputs from Biomechanics and Modeling in Mechanobiology
#422
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Outputs of similar age
#223,080
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Outputs of similar age from Biomechanics and Modeling in Mechanobiology
#7
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